Research on Optimization of Deformable Robot Walking Mechanism Based on Machine Learning

Deformable walking mechanisms have a wide range of applications in complex environments, but traditional designs suffer from adaptability issues. To address this challenge, we propose a novel deformable walking mechanism design. By optimizing the mechanical structure, control algorithm, and material selection, we significantly improve the mechanism's deformability, walking performance, and terrain adaptability. Experimental results show that our mechanism outperforms traditional rigid walking mechanisms in terms of speed, energy efficiency, and stability. This research provides a new perspective on mobile robot design and is expected to play a crucial role in rescue, exploration, and other fields. Future research will focus on enhancing the mechanism's intelligence and environmental perception capabilities.